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Performance Evaluation of Parametric and Nonparametric Methods When Assessing Effect Measure Modification.

Authors :
Rodriguez, Gabriel Conzuelo
Bodnar, Lisa M
Brooks, Maria M
Wahed, Abdus
Kennedy, Edward H
Schisterman, Enrique
Naimi, Ashley I
Source :
American Journal of Epidemiology. Jan2022, Vol. 191 Issue 1, p198-207. 10p.
Publication Year :
2022

Abstract

Effect measure modification is often evaluated using parametric models. These models, although efficient when correctly specified, make strong parametric assumptions. While nonparametric models avoid important functional form assumptions, they often require larger samples to achieve a given accuracy. We conducted a simulation study to evaluate performance tradeoffs between correctly specified parametric and nonparametric models to detect effect modification of a binary exposure by both binary and continuous modifiers. We evaluated generalized linear models and doubly robust (DR) estimators, with and without sample splitting. Continuous modifiers were modeled with cubic splines, fractional polynomials, and nonparametric DR-learner. For binary modifiers, generalized linear models showed the greatest power to detect effect modification, ranging from 0.42 to 1.00 in the worst and best scenario, respectively. Augmented inverse probability weighting had the lowest power, with an increase of 23% when using sample splitting. For continuous modifiers, the DR-learner was comparable to flexible parametric models in capturing quadratic and nonlinear monotonic functions. However, for nonlinear, nonmonotonic functions, the DR-learner had lower integrated bias than splines and fractional polynomials, with values of 141.3, 251.7, and 209.0, respectively. Our findings suggest comparable performance between nonparametric and correctly specified parametric models in evaluating effect modification. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00029262
Volume :
191
Issue :
1
Database :
Academic Search Index
Journal :
American Journal of Epidemiology
Publication Type :
Academic Journal
Accession number :
154736378
Full Text :
https://doi.org/10.1093/aje/kwab220